reinforcement learningfamily
IMPALA
Scalable distributed deep reinforcement learning architecture with importance-weighted actor-learners. Paper by Espeholt et al. (2018).
Levelfamily
Classreinforcement learning
Parametersnot in the notes
Contextnot in the notes
Released5 Feb 2018
Opennessunknown
Runs onnot in the notes
Statusactive
Identity
- Developer
- Google DeepMind
- Family
- not in the notes
- Released
- 5 Feb 2018 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- other Distributed actor-learner architecture with V-trace off-policy correction
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- not in the notes
- Output
- action
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Implemented in RLlib (Ray). model_class left empty: AURION has no reinforcement learning class yet.
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelIMPALAGoogle DeepMind, reinforcement learning
IMPALAGoogle DeepMind, reinforcement learningUse Casesnone recorded
Who Runs Itnone recorded
Organisations 1
Sources
- arxiv.org/abs/1802.01561 https://arxiv.org/abs/1802.01561
- docs.ray.io/en/latest/rllib/rllib-algorithms.html https://docs.ray.io/en/latest/rllib/rllib-algorithms.html
- arxiv.org/html/1802.01561 https://arxiv.org/html/1802.01561
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "IMPALA", https://aurion.semai.id/models/impala/, records of October 2026.